一种针对走私檀香的武器监控红外图像检测系统模型

S. Mohan Sai, K. Naresh, S. Rajkumar, Mohan Sai Ganesh, Lok Sai, A. Nav
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引用次数: 4

摘要

檀香是世界上最有价值的树木之一。檀香木抢劫案日益增多,因为没有足够的安全保障。最终他们得到了我国最濒危的树木之一。因此,为了保护树木,本文提出了一种使用inception-v3模型的方法。主要目的是探测森林中是否有人,特别是在有限的时间内。红外图像的重要性在于,即使在夜间(即即使没有光线)也可以看到这些图像。主要作用是创建一个分类器来检测人持有的武器类型。本文基于Inception-v3模型的tensorflow。利用迁移学习技术对红外图像进行再训练。基于“陆战武器红外数据库”下的OTCBVS基准数据集实现。本文提出了一个准确率达到99%的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Infrared Image Detecting System Model to Monitor Human with Weapon for Controlling Smuggling of Sandalwood Trees
Sandalwood is one of the most valuable trees in the world. Sandalwood robberies are increasing day by day as there isn't enough security being provided for them. Eventually they are getting one of the most endangered trees in our country. So, to protect the trees, in this paper proposed a method using inception-v3 model. The main objective is to detect if there is any person in the forest particularly in the restricted time. The importance of infrared images are that these can be visible even in the night time (i.e. even if no light). The main role is to create a classifier which detects the type of weapon hold by the person. This paper is based on Inception-v3 model of tensorflow. We use the technique transfer learning to retrain the infrared images. The implementation is done based on benchmark dataset OTCBVS under “Terravic Weapon Infrared Database”. This paper propose a model with the 99% accuracy.
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